2023 AIChE Annual Meeting

Session: Particulate Process Modeling and Product Design

Chair

Rohit Ramachandran, Rutgers The State University of New Jersey

Co-Chair

Presentations

12:30 PM

(333a) Semi-Mechanistic Prediction of Residence Time Metrics and Mixing Dynamics in Single-Screw Extrusion Via a 2-D Convection-Diffusion Model Combined with Machine Learning
Ashley Dan, Rohit Ramachandran, Erik Holmen Olofsson, Jesper H. Hattel, Ninna H. Jokil, Shashank V. Muddu

12:48 PM

(333b) Development of High-Speed Computing Method for Powder Mixing Using Machine Learning with Random Model
Naoki Kishida, Hideya Nakamura, Shuji Ohsaki, Satoru Watano

01:06 PM

(333c) High Order Mass Preserving Finite Volume Approach for Rennet-Induced Coagulation Equation
Mehakpreet Singh

01:24 PM

(333d) Super Learner Based Recurrent Neural Network Modelling Twin-Screw Granulation
James D. Litster, Kai Liu, Mahdi Mahfouf, Daniel Coca

01:42 PM

(333e) Predicting Drying Performance of Pharmaceutical Spray Dryers By Means of Multiphysics Simulations
Ute Lander, Florian Ries, Mike Weinberg, Ali Guerbuez, Andreas Thomann, Regina Reul, Andreas Gryczke

02:00 PM

(333f) Design Space Optimization of a Sachet Filling Device Using Discrete Element Method (DEM)
Amir Esteghamatian, Matthew Santangelo, Hong-Guann Lee, Rolf Larsen, Jordan Arcangel, Diogo Gomes Lopes, Mario Schaefer, Daniel O. Blackwood, Pankaj Doshi

02:18 PM

(333g) A Hybrid Multivariate Model for Understanding Fluid Bed Wet Granulation Process Parameters Impact on Tablet Physicals
Sydney Butikofer, Maitraye Sen, Salvador García-Muñoz

02:36 PM

(333h) Utilising Science-Based Compaction Models for Drug Product Development: Tech Transfer and Flowsheet Simulations
Lok Hang Wong, Stefan Bellinghausen, Dana Barrasso, Robert Yule, Abhishek Paul, Mario Rousselin-Morales, Yasser Jangjou, Indu Muthancheri, Nicolas Sanchez, Ananya Chowdhury, Yash Melkeri